WO2022196080A1

WO2022196080A1 - Information processing device, information processing method, program, moving device, and information processing system

Info

Publication number: WO2022196080A1
Application number: PCT/JP2022/001718
Authority: WO
Inventors: 英一郎森永; 淳一郎三澤; 達也石川
Original assignee: ソニーグループ株式会社
Priority date: 2021-03-16
Filing date: 2022-01-19
Publication date: 2022-09-22

Abstract

The present disclosure pertains to an information processing device, information processing method, program, moving device, and information processing system that make it possible to estimate a self-location and orientation at high accuracy and a smaller calculation load. The present invention provides an information processing device which comprises at least two absolute-position sensors, and a self-location/orientation calculation unit that calculates self-location and orientation. The self-location/attitude calculation unit calculates self-location and orientation on the basis of an absolute position acquired from the absolute-position sensors and the relative positions of the absolute-position sensors with respect to a reference position of the moving device. The present disclosure can be applied, for example, to an autonomous mobile robot device.

Description

Information processing device, information processing method, program, mobile device, and information processing system

TECHNICAL FIELD The present disclosure relates to an information processing device, an information processing method, a program, a mobile device, and an information processing system, and in particular, it is possible to estimate a self position and orientation with higher accuracy with less computational load, for example. The present invention relates to an information processing device, an information processing method, a program, a mobile device, and an information processing system.

In recent years, research and development of robots with autonomous movement functions have been actively carried out. This type of autonomous mobile robot must have a function of estimating its own position, which indicates where it is now.

As a technology related to self-location estimation, for example, there is a technology disclosed in Patent Document 1. In Patent Document 1, an omnidirectional predicted image is created by synthesizing an omnidirectional image obtained when the robot is placed at an initial position, assuming that the robot has moved from the initial position. and an omnidirectional image newly obtained by the actual movement of the robot to detect the position and orientation of the robot.

JP-A-2006-220521

When estimating the self-position of an autonomous mobile robot, it is required to estimate the self-position and posture with high precision with a small computational load. In the technique disclosed in Patent Document 1, when estimating the self-position of the robot, the captured image captured by the camera is used, so the computational load in the image processing increases.

The present disclosure has been made in view of such circumstances, and is intended to enable estimation of the self-position and orientation with less computational load and with higher accuracy.

An information processing apparatus according to one aspect of the present disclosure includes at least two absolute position sensors and a self-position/orientation calculation unit that calculates a self-position and orientation, and the self-position/orientation calculation unit obtains information from the absolute position sensor. and the relative position of the absolute position sensor with respect to the reference position of the mobile device.

An information processing method and program according to one aspect of the present disclosure are an information processing method and program corresponding to the information processing apparatus according to one aspect of the present disclosure described above.

In the information processing device, information processing method, and program according to one aspect of the present disclosure, based on the absolute positions obtained from at least two absolute position sensors and the relative positions of the absolute position sensors with respect to the reference position of the mobile device, Self position and pose are calculated.

A mobile device according to one aspect of the present disclosure is based on at least two or more absolute position sensors, the absolute positions acquired from the absolute position sensors, and the relative positions of the absolute position sensors with respect to the own reference position. and a control unit that calculates an attitude.

In the mobile device according to one aspect of the present disclosure, at least two absolute position sensors are provided. and attitude are calculated.

An information processing system according to one aspect of the present disclosure includes a moving device and an absolute position detection mat on which a predetermined pattern indicating an absolute position is formed, wherein the moving device includes at least two absolute position sensors; a controller for calculating a self-position and orientation based on the absolute position obtained from the absolute position sensor and the relative position of the absolute position sensor with respect to the self-reference position, wherein the mobile device is for detecting the absolute position; The information processing system identifies the absolute position by recognizing the pattern with the absolute position sensor when the object exists on the mat.

In the information processing system of one aspect of the present disclosure, when the mobile device is present on the absolute position detection mat, the absolute position is specified by recognizing the pattern by at least two or more absolute position sensors. The self-position and orientation are calculated based on the absolute position and the relative position of the absolute position sensor with respect to the self-reference position.

It should be noted that the information processing device or mobile device according to one aspect of the present disclosure may be an independent device, or may be an internal block forming one device.

1 is a diagram illustrating a first example of an external configuration of a robot device to which the present disclosure is applied; FIG. FIG. 4 is a diagram showing a second example of the configuration of the appearance of a robot device to which the present disclosure is applied; 1 is a diagram illustrating an example of components of a robot apparatus to which the present disclosure is applied; FIG. FIG. 4 is a diagram showing an example of a movable screen in a robot device to which the present disclosure is applied; FIG. 4 is a diagram showing a first example of cooperative motion by a plurality of robot devices; FIG. 10 is a diagram illustrating a second example of cooperative motion by a plurality of robot devices; FIG. 11 is a diagram illustrating a third example of cooperative motion by a plurality of robot devices; FIG. 11 is a diagram showing a fourth example of cooperative motion by a plurality of robot devices; FIG. 4 is a diagram showing an example of position measurement using a plurality of optical absolute position sensors in a robot device to which the present disclosure is applied; 1 is a block diagram showing an example of a functional configuration of a robot device to which the present disclosure is applied; FIG. FIG. 4 is a diagram showing an example of arrangement of a plurality of optical absolute position sensors; FIG. 10 is a diagram showing another example of arrangement of a plurality of optical absolute position sensors; FIG. 10 is a diagram showing an example of a method of calculating self-position and orientation using measurement results from a plurality of optical absolute position sensors; It is a figure which shows the usage example of the robot apparatus to which this indication is applied. It is a block diagram which shows the example of a structure of a computer.

<1. Embodiment of the Present Technology>

(External configuration)
1 and 2 show an example of an external configuration of a robot device to which the present disclosure is applied. FIG. 1 shows a top view, a front view, and a side view of a robot device to which the present disclosure is applied. FIG. 2 shows a state in which the display in the robot device to which the present disclosure is applied is moved.

The robot device 10 is an autonomous robot. Further, the robot apparatus 10 is a mobile robot (autonomous mobile robot) having a mobile mechanism such as wheels, and can freely move in space.

The robot device 10 has a substantially rectangular parallelepiped shape, and has a display capable of displaying display information such as images on its upper surface. In the robot device 10, the display (screen) on the upper surface is movable, and can be adjusted to a desired angle with respect to a plane (a moving surface such as a floor surface or the ground), and its posture can be fixed.

(Component)
FIG. 3 shows an example of components of a robot device to which the present disclosure is applied. In FIG. 3, the robot apparatus 10 includes a control unit 101 for controlling the operation of each part, an image display unit 102 including a display for displaying images, and a screen elevation mechanism including a mechanism for raising and lowering the image display unit 102. and a unit 103 . In the following description, the physical structural portion of the robot device 10 is also referred to as the body.

In FIG. 3, a thin plate-like image display unit 102 provided on the upper surface of the housing of the robot device 10 is moved by a screen lifting unit 103 and fixed in a desired posture. Thus, in the robot apparatus 10, the image display unit 102 can move around its lower end portion, and when the image display unit 102 opens upward, the inside of the housing is exposed to the outside.

The robot device 10 has a left motor encoder 104-1 and a left motor 105-1, and a right motor encoder 104-2 and a right motor 105-2. The robot apparatus 10 employs a differential two-wheel drive type, and the left and right motors 105-1 and 105-2 operate to enable movement by the left and right wheels. The left motor encoder 104-1 and the right motor encoder 104-2 detect the amount of rotational movement of the left motor 105-1 and the right motor 105-2.

The robot device 10 has various sensors such as sensors 106-1 to 106-3. The sensors 106-1 to 106-3 include IMU (Inertial Measurement Unit), LiDAR (Light Detection and Ranging), position sensors, cameras, and the like. The robot apparatus 10 operates as an autonomous mobile robot using sensor signals detected by various sensors. The battery unit 107 supplies electric power to each part of the robot device 10 .

(Movable screen movable)
FIG. 4 shows an example in which a movable display (movable screen) in the robot device 10 is moved. In FIG. 4, it is assumed that the robot device 10 is used on a court for playing sports. In this case, the robot device 10 changes the posture of (the display of) the image display unit 102 according to the situation such as its own position and posture, and the position of the target spectators (spectators watching the game on the court). , can be adjusted to the desired posture.

For example, if there are 1st floor seats and 2nd floor seats as spectator seats for watching a game on the court, the robot device 10 presents an image to the spectators on the 1st floor and 2nd floor seats. The posture of (the display of) the image display unit 102 is changed when the image is presented to the audience.

Specifically, since the spectators on the second floor are spatially higher than the spectators on the first floor, the tilt of the image display unit 102 is adjusted so as to be gentler according to the line of sight of the spectators. . Conversely, for spectators on the first floor, the inclination of the image display unit 102 may be adjusted to be steeper. In addition, when targeting all the spectators around the court (360-degree spectators), the robot device 10 does not tilt the image display unit 102 (the screen of the display is displayed on the floor, the ground, etc.). (parallel to the plane of movement of the screen) so that all spectators in the surroundings have their eyes directed to the screen.

(Coordinated motion of multiple robots)
FIGS. 5 to 8 show an example in which a plurality of robot devices 10 cooperate to form a pseudo screen having a predetermined shape.

In FIG. 5, eight robot devices 10-1 to 10-8 perform cooperative operations and are arranged in two rows and four columns (2×4), so that the display (2×4 screen) of each robot device 10 is displayed. are combined to configure one screen (large screen) having a pseudo predetermined shape. Using this large screen (2×4 screen), one large image can be presented to the audience.

In FIG. 6, eight robot devices 10-1 to 10-8 perform coordinated operations and are arranged in one row and eight columns (1×8), so that the display (1×8 screen) of each robot device 10 is displayed. are combined to construct one pseudo-screen (landscape screen). Using this large screen (1×8 screen), one horizontally long image can be presented to the audience.

At this time, as shown in FIG. 7, the robot devices 10-1 to 10-8 change the posture of (the display of) the image display unit 102 according to the situation such as the position and posture of the robot device and the position of the target audience. It can be adjusted to the desired posture. In addition, as shown in FIG. 7, in the robot devices 10-1 to 10-8, all of the image display units 102 are tilted at the same angle. The image display unit 102 may be tilted at different angles.

(Measurement using multiple optical absolute position sensors)
The robot apparatus 10 estimates its own position and orientation based on absolute positions measured by a plurality of optical absolute position sensors during autonomous movement. FIG. 9 shows an example of measurement using four optical absolute position sensors 161-1 to 161-4 as the plurality of optical absolute position sensors in the robot apparatus 10. FIG.

Here, the absolute position sensor is a sensor that can measure the absolute position. That is, the absolute position sensor does not measure the distance from one point to the next point, but can measure the position of a certain point only by measuring that point. Among absolute position sensors, an optical absolute position sensor measures an absolute position by detecting light from an object such as visible light and infrared rays. For example, an optical absolute position sensor identifies a position (measures an absolute position) within a predetermined area such as on a court by reading unique information from a predetermined pattern.

In addition, since the accuracy of the absolute position sensor depends on the fineness of a predetermined pattern, the accuracy of posture estimation by one absolute position sensor does not meet the accuracy required for the robot apparatus 10 to travel over a wide area such as on a court. On the other hand, it is extremely low, and it is difficult for the robot device 10 to travel over a wide area using a single absolute position sensor.

The robot device 10 can measure the absolute position by reading a predetermined pattern formed on the absolute position detection mat 20 by each of the plurality of optical absolute position sensors 161 installed on the bottom surface of the robot device 10 . Here, the optical absolute position sensor 161 is installed at a position relative to a reference position on the bottom surface of the robot apparatus 10 and at a position where a predetermined pattern formed on a moving surface facing the bottom surface can be recognized.

Based on the absolute positions obtained from each of the plurality of optical absolute position sensors 161 and the relative position of each optical absolute position sensor 161 with respect to the reference position of the bottom surface, the robot apparatus 10 can determine its own position and posture with higher accuracy. can be calculated.

The absolute position detection mat 20 is installed on a moving surface such as a floor on which the robot device 10 can move. A predetermined pattern indicating an absolute position is formed on the surface of the mat 20 for absolute position detection, and the absolute position can be designated using XY coordinates or the like. For example, a predetermined pattern indicating the absolute position can be printed on the surface of the mat 20 for absolute position detection. The mat 20 for absolute position detection only needs to have a vertical and horizontal size that can accommodate most of the body when the robot device 10 is placed thereon. It is possible to measure the absolute position even if it becomes a posture.

For example, when the robot device 10 is used on a court, the absolute position detection mat 20 needs to be installed in accordance with the area of the court. Further, by using a transparent mat that can reflect infrared rays and has a pattern (infrared pattern) indicating an absolute position as the mat 20 for absolute position detection, when the mat is attached to a moving surface such as a floor, It is possible to prevent spectators from noticing the presence of the absolute position detection mat 20.例文帳に追加

Here, the advantages of using the plurality of optical absolute position sensors 161 in the robot device 10 will be explained in comparison with the case of using other sensors, for example, as follows.

Since the optical absolute position sensor can directly measure the absolute position, the calculation load is smaller than when using other sensors, and even if multiple sensors are installed, the calculation processing load is low. Therefore, in the robot apparatus 10, a low-cost computer can be used as a computer for performing calculation processing.

On the other hand, when a camera is used to detect the absolute position, although it is possible to perform detection with high accuracy, the computational load is high, and in general small robot devices require high performance for image processing. It is difficult to install multiple computers because it requires a large number of computers. In addition, when using a single camera, the camera mounting error directly becomes the self-position error (displacement of the initial position and attitude). It will be reflected as it is.

When estimating the self-position of robots, internal sensors such as wheel speed sensors and IMUs are mainly used when it is not possible to install large-scale equipment on the court or its surroundings. The actual position will deviate due to the influence of IMU integration error. Therefore, a method of correcting the self-position by measuring the position of the body by recognizing a two-dimensional code or the like with a camera is generally used to compensate for the deviation of the self-position by an internal sensor in the environment.

When the position of the robot device is greatly deviated from the position of the 2D code, if the angle of view of the camera is not sufficiently large, the 2D code cannot be captured and the self position cannot be corrected. On the other hand, if the angle of view of the camera is increased, the accuracy will decrease. Furthermore, if the number of pixels is increased in order to compensate for the decrease in accuracy, the calculation load will increase.

Also, when a camera is installed on the bottom side of the robot device and the moving surface is photographed, it is difficult to read the two-dimensional code unless lighting is used to provide appropriate brightness. In the case of using a camera, an error occurs in the self-position unless the distortion of the camera lens is properly corrected. Accurate position estimation requires calibration for camera correction, but this type of calibration takes time and effort.

In this way, in the case of a system using a camera for detecting the absolute position, there are problems such as the load on the image processing of the camera, the installation accuracy of the camera, lighting and calibration, so the robot to which the present disclosure is applied Device 10 uses an optical absolute position sensor.

However, when using an optical absolute position sensor that measures the absolute position from a predetermined pattern formed on a moving surface such as the floor, the computational load is small, but the accuracy is low, and the robot device must operate with high accuracy. is difficult to use. In other words, the accuracy of estimating the self-position of the robot apparatus is lower than that of a system using a camera when the optical absolute position sensor is used alone.

Therefore, in the robot apparatus 10 to which the present disclosure is applied, a predetermined pattern indicating the absolute position formed on the absolute position detection mat 20 is detected by a plurality of optical absolute position sensors 161 respectively installed at relative positions with respect to the reference position. Reading it causes the absolute position to be measured. In addition, by performing appropriate calculation processing on the low-precision absolute position information obtained from a plurality of optical absolute position sensors 161, even if the optical absolute position sensor 161 has a low accuracy by itself, a plurality of sensors can be installed. By doing so, it is possible to estimate the self-position and orientation with high accuracy while keeping the computational load small.

(Functional configuration)
FIG. 10 shows an example of a functional configuration of a robot device to which the present disclosure is applied.

The robot device 10 has a main CPU (Central Processing Unit) 151 and a sensor 152 . The main CPU 151 is included in the control unit 101 of FIG. 3, for example. The main CPU 151 has a self-position/orientation calculator 171 and a controller 172 . The sensor 152 has optical absolute position sensors 161-1 to 161-N (N is an integer equal to or greater than 2).

The optical absolute position sensor 161-1 is installed at a predetermined position on the bottom surface of the robot device 10. The optical absolute position sensor 161-1 identifies the absolute position indicated by the recognized pattern by recognizing a predetermined pattern formed on the moving surface while the robot device 10 is running or stopped. The optical absolute position sensor 161 - 1 supplies information about the identified absolute position to the self-position/orientation calculator 171 .

The optical absolute position sensors 161-2 to 161-N are configured in the same manner as the optical absolute position sensor 161-1, and are installed at predetermined positions on the bottom surface of the robot device 10, respectively. Each of the optical absolute position sensors 161-2 to 161-N, when the robot device 10 is running or stopped, automatically transmits information about the absolute position specified by recognizing a predetermined pattern formed on the moving surface. It is supplied to the position/orientation calculation unit 171 .

The self-position/orientation calculation unit 171 acquires information about the absolute position supplied from each of the optical absolute position sensors 161-1 to 161-N. The information about the absolute position can be coordinates represented by the XY coordinate system, an ID (position ID) for identifying the target position, or the like. In addition, the self-position/orientation calculation unit 171 holds in advance information on the relative positions of the bottom surface of the robot device 10 relative to the reference position for each of the optical absolute position sensors 161-1 to 161-N installed on the bottom surface of the robot device 10. is doing.

The self-position/orientation calculator 171 determines the position of the robot based on the absolute positions obtained from each of the plurality of optical absolute position sensors 161 and the relative positions of the optical absolute position sensors 161 with respect to the reference position on the bottom surface of the robot apparatus 10. The self-position and orientation of the device 10 are calculated. The self-position/orientation calculation unit 171 supplies information about the calculated self-position and orientation to the control unit 172 .

The control section 172 controls the operation of each section of the robot device 10 . The control unit 172 acquires information about the self-position and orientation supplied from the self-position/posture calculation unit 171 . The control unit 172 performs control to autonomously move the robot apparatus 10 based on its own position and orientation.

In the robot apparatus 10 configured as described above, the self-position/orientation calculator 171 calculates the absolute positions obtained from at least two or more optical absolute position sensors 161 and the relative positions of the optical absolute position sensors 161 with respect to the reference position of the bottom surface. Based on the position, the self-position and orientation are calculated. Since the absolute position measured by the optical absolute position sensor 161 and the relative position stored in advance are used when calculating the self position and orientation, there is no need to perform processing with a high computational load such as image processing. , a process with a lower computational load (for example, an arithmetic process such as addition or multiplication) may be performed. Moreover, by measuring the absolute position using a plurality of optical absolute position sensors 161, the accuracy of the self-position and orientation can be improved. Therefore, the robot apparatus 10 to which the present disclosure is applied can estimate its own position and orientation with less computational load and with higher accuracy.

(Sensor arrangement example)
FIG. 11 shows an example of arrangement of a plurality of optical absolute position sensors 161. As shown in FIG. 11A and 11B show a side view and a bottom view of the robot device 10. FIG. In practice, a movement mechanism such as wheels is provided on the bottom surface of the robot device 10, but the illustration is omitted in order to make the arrangement of the sensors easier to understand.

As shown in FIG. 11B, on the bottom surface of the robot device 10, four sensors, optical absolute position sensors 161-1 to 161-4, are arranged side by side in the longitudinal direction of the bottom surface with respect to the reference position. . For example, when the position of the robot device 10 on the court is defined as the center (center of gravity) of the bottom surface of the machine body, the center of the bottom surface of the machine body is the reference position. Note that the reference position is not limited to the center of the bottom surface of the fuselage, and may be another position such as the upper left of the bottom surface of the fuselage.

Although each of the optical absolute position sensors 161-1 to 161-4 has lower accuracy than a system using a camera, each optical absolute position sensor 161 outputs an absolute position as a measurement result. Even when installed, the computational load does not increase so much that it is necessary to use a high-performance computer. As shown in FIG. 11, when the optical absolute position sensors 161-1 to 161-4 are arranged in the longitudinal direction with respect to the reference position on the bottom surface, the value in the longitudinal direction (y direction) is fixed. can be performed, the amount of calculation can be further reduced.

In addition, since the optical absolute position sensors 161-1 to 161-4 are arranged at positions relative to the reference position on the bottom surface of the robot device 10, and information about the inclination measurable by each optical absolute position sensor 161 is not used. By measuring and holding the relative positions of the optical absolute position sensors 161-1 to 161-4 in advance, the self position and orientation can be calculated using the measured absolute positions. In addition, since the robot apparatus 10 uses an infrared absolute position sensor as the optical absolute position sensor 161, it is not necessary to provide a separate illumination or perform calibration compared to a system using a camera. becomes unnecessary.

FIG. 11B is an example of the arrangement of the plurality of optical absolute position sensors 161. The number and arrangement of the sensors are arbitrary, and other arrangements may be adopted. The greater the number of optical absolute position sensors 161, the more widely they can be distributed on the bottom surface of the robot device 10, and thus the more errors can be reduced.

FIG. 12 shows another example of the arrangement of the plurality of optical absolute position sensors 161. FIG. Similar to FIG. 11B, FIGS. 12A to 12C show bottom views of the robot apparatus 10. FIG.

In FIG. 12A, the optical absolute position sensors 161-1 to 161-4 are arranged side by side in the longitudinal direction with respect to the reference position of the bottom surface (for example, the center of the bottom surface), similar to the arrangement of FIG. 11B. However, the spacing between the sensors is different. By arranging the optical absolute position sensors 161-1 to 161-4 in a straight line, the calculation load can be reduced.

In FIG. 12B, the optical absolute position sensors 161-1 and 161-2 are arranged at relative positions with respect to the reference position of the bottom surface (for example, the center of the bottom surface). The number of optical absolute position sensors 161 should be at least two, and the greater the distance between the sensors, the higher the accuracy of the posture (angle) of the robot device 10 can be.

In FIG. 12C, the optical absolute position sensors 161-1 to 161-8 are arranged in 2 rows and 4 columns (2×4) with respect to the reference position of the bottom surface (for example, the center of the bottom surface). By increasing the number of optical absolute position sensors 161, both the accuracy of the position and orientation (angle) of the robot device 10 can be improved.

(Calculation example of self-position and posture)
Next, an example of calculation of the self-position and posture by the self-position/posture calculation unit 171 will be described. FIG. 13 shows the absolute position (position P _N ) measured by the optical absolute position sensor 161 and the self position/orientation calculation when calculating the self position and orientation using the measurement results of the plurality of optical absolute position sensors 161 . The relationship with the self-position (position P _T ) calculated by the unit 171 is shown. In this example, since the robot device 10 is positioned at the center of the bottom surface of the machine body, the center of the bottom surface of the machine body is the reference position.

The self-position/orientation calculation unit 171 calculates the minimum distance between the position P _N measured by each optical absolute position sensor 161 and the position P _T (x, y, θ) as the true position and orientation of the robot device 10 . By applying multiplication, an optimization calculation is performed to estimate the values of x, y, and θ that minimize the error.

Here, focusing on the first optical absolute position sensor 161 among the plurality of optical absolute position sensors 161, the position P ₁ (x _g1 , y _g1 ) from the center of the bottom surface of the airframe is given by the following equation: (1). However, in Equation (1), the values of x ₁ and y ₁ are known values measured in advance.

Further, when the position P _N of the optical absolute position sensor 161 measured at the Nth position is (x _mn , y _mn ), the error between the measured value and the estimated value is expressed by the following equation (2). be. However, in equation (2), x _mn and y _mn are measured values representing the actually measured absolute positions, and x _gn and y _gn are theoretically calculated from the position _PT to be estimated from now on. position of the sensor.

Here, if the number of optical absolute position sensors 161 installed on the bottom surface of the robot device 10 is used to sum equation (2), it is expressed by the following equation (3).

By finding a combination of x, y, and θ values that minimize Equation (3), the values of x, y, and θ that minimize the error between the measured value and the estimated value are calculated.

Here, it can be assumed that the initial installation error of the robot device 10 and the deviation of the yaw angle due to the drift of the gyro sensor mounted on the robot device 10 are extremely small. Therefore, by approximating cos θ = 1, sin θ = θ and performing linearization, it is possible to apply the least squares method.

That is, the three expressions shown in Expression (4) can be expressed by the following Expressions (5), (6), and (7), respectively.

The final results of formulas (5), (6), and (7) are summarized in the following formula (8).

Formula (8) is expressed as the following formula (9) by expanding and summarizing.

By substituting the actually measured values (x _mi , y _mi ) in Equation (9), the values of x, y, and θ can be obtained. Then, the combination of these values _minimizes the error between the measured value and the estimated value. become.

Here, equation (9) is a simple three-dimensional first-order simultaneous equation including addition and multiplication, so a solution can be obtained with a smaller computational load. Furthermore, even if the number of optical absolute position sensors 161 installed in the robot device 10 is increased, if the position of the bottom surface of the machine body on which the optical absolute position sensors 161 are installed is known, the equation (9) is similarly applied. can do.

Also, the actually measured values (x _mi , y _mi ) contain only information about the absolute position (not including information about the tilt), but the self-position is only the position (x, y). can also estimate the orientation (θ). In the above description, the case of using the least squares method was exemplified. However, if the least squares method is not used, nonlinear optimization calculations must be performed, resulting in high calculation costs.

(Example of use of robot device)
FIG. 14 shows a usage example of the robot device 10 to which the present disclosure is applied.

In FIG. 14, a scene is assumed in which a plurality of robot devices 10 are synchronized in a basketball court 30 and perform performances by coordinated actions such as running and lining up. Each robot device 10 has an autonomous movement function, but is equipped with an internal sensor such as a wheel speed sensor and an IMU, and does not have means for recognizing an absolute position with respect to the court 30 .

An absolute position detection mat 20 is fixed to a specific area (starting point, etc.) within the court 30 by being aligned with the court 30 and pasted. Each of the robot devices 10-1 to 10-8 placed outside the court 30 is placed on the absolute position detection mat 20 in order from the robot device 10-1 before starting its operation, and the user U turns on the switch. An operation such as pressing is used as a trigger to start measuring the initial position and orientation.

In the robot device 10-1, the measurement values obtained by reading the predetermined pattern printed on the absolute position detection mat 20 by the plurality of optical absolute position sensors 161 are used as the self-position and orientation calculation method described above. is used to calculate the self-position and attitude (x, y, θ) obtained by integration, and recorded in the memory as the initial position and attitude of the aircraft with respect to the court 30 . Then, the robot device 10-1 that has recorded the initial position and posture generates route information regarding a route toward a predetermined position (such as the starting point of the performance) within the court 30 based on the initial position and posture at that time. do. The robot device 10-1 travels toward a predetermined position within the court 30 based on the generated route information.

Next to the robot device 10-1, the robot devices 10-2 to 10-8 are placed on the absolute position detection mat 20 in order. In each of the robot devices 10-2 to 10-8, similar to the robot device 10-1, the initial position and orientation of the machine body are calculated based on the measurement values measured by the plurality of optical absolute position sensors 161. , route information is generated, and the player runs toward a predetermined position (such as a starting point of the performance) within the court 30 .

As a result, each of the robot devices 10-1 to 10-8 sequentially travels toward a predetermined area within the court 30 and automatically aligns. Since the initial positions and postures of the robot devices 10-1 to 10-8 are matched, they can act in coordination to perform performances (eg, the coordinated motions shown in FIGS. 5 to 8).

In this way, by simply placing a plurality of robot devices 10 on the absolute position detection mat 20 in sequence and pressing a switch by the user U, each robot device 10 can detect the position of the machine body (own machine) on the court 30 . and posture can be recognized. At that time, even if the absolute position detection mat 20 were fixed to the court 30 with a deviation, since all the robot devices 10 have the same error, there is no relative error, and synchronization is possible. It does not affect predetermined actions (such as performances by coordinated actions).

Further, in the above description, an example was shown in which the performances of the plurality of robot devices 10 were matched by matching the initial positions and postures of the plurality of robot devices 10. It is also possible to correct deviations in coordinated motions of a plurality of robot devices 10 during the performance by fixing the robot devices 10 to a predetermined area in the mat and running on the mat during the performance.

When determining the initial position and orientation of the robot device by measurement using a camera and a two-dimensional code to detect the absolute position, image processing of the image taken by the camera is burdensome, so computational processing capacity is limited. Such a technique cannot be used in a robotic device that is not abundant in power. Therefore, at present, the initial position and posture of the robot device are adjusted manually or by using a jig (positioning jig) capable of regulating the position of the robot device.

However, when it is done manually, the error is large, and when multiple robot devices are moved at the same time, it is difficult to realize the movement of all the robot devices neatly. In addition, if a jig is used, the jig becomes large, and in the case of a differential two-wheel drive type robot device, it cannot be moved in the left-right direction. It took time and effort to install the

Therefore, even if the robot device is placed appropriately to some extent, there is a need for a method in which the robot device autonomously recognizes the initial position and posture of the body and estimates the absolute position in the court. proposed a method to calculate the initial position and attitude of the airframe.

<2. Variation>

In the above description, the differential two-wheel drive type was exemplified as the drive type of the robot device 10, but other drive types such as an omnidirectional movement type may be used.

Further, in the above description, in the robot apparatus 10, when changing the attitude of the image display unit 102 including the display, the case of driving along one axis was exemplified. may Display information to be displayed on the display is not limited to video, and may be information such as images and text.

The robot device 10 to which the present disclosure is applied can be regarded as an autonomous mobile device having a control unit such as the control unit 101. The control unit is configured as an information processing device having a processor such as a CPU, and may be provided inside the robot device 10 or may be configured as an external device. Further, it may be considered that an information processing system is configured by the robot device 10 to which the present disclosure is applied and the absolute position detection mat 20 .

Also, the robot device 10 to which the present disclosure is applied can be regarded as a system (autonomous movement system) in which multiple devices such as a control device, a sensor device, a display device, a communication device, and a movement mechanism are combined. Here, a system means a set of a plurality of constituent elements (devices, modules (parts), etc.), and it does not matter whether or not all the constituent elements are in the same housing. Therefore, a plurality of devices housed in separate enclosures and connected via a network, and a single device housing a plurality of modules within a single enclosure, are both systems.

In addition, the robot device 10 to which the present disclosure is applied can further include an attachment for cleaning. This cleaning attachment is in the form of a mop, and is attached to the front, rear, side, bottom, etc. of the robot device 10 so that the robot device 10 can autonomously travel to clean the travel route. can be done. The location to be cleaned may be given in advance as a travel route, or may be cleaned by recognizing an instruction such as "clean this area" from the instructor by gesture recognition. As for this gesture recognition, the gesture of the target is recognized by recognizing the posture, movement, etc. of the target indicator based on the sensor signal from the sensor 106 (camera or the like).

Furthermore, the cleaning operation and the image display may be performed in cooperation. In this case, when cleaning is started, during cleaning, and when cleaning is completed, a video display to that effect may be performed, or an advertisement or other video display may be performed during cleaning. Furthermore, the attitude of (the display of) the video display unit 102 may also be controlled. Also, the cleaning attachment is not limited to the illustrated mop-shaped one, and includes other types such as a dustpan-shaped one.

<3. Computer Configuration>

A series of processes in estimating the self-position and orientation described above can be executed by hardware or by software. When executing the series of processes by software, a program constituting the software is installed in the computer of each device.

FIG. 15 is a block diagram showing an example of the hardware configuration of a computer that executes a series of processes in estimating the self-position and orientation described above by means of a program.

In computer 1000 , CPU 1001 , ROM (Read Only Memory) 1002 and RAM (Random Access Memory) 1003 are interconnected by bus 1004 . An input/output interface 1005 is further connected to the bus 1004 . An input unit 1006 , an output unit 1007 , a recording unit 1008 , a communication unit 1009 and a drive 1010 are connected to the input/output interface 1005 .

The input unit 1006 consists of various sensors, microphones, switches, and the like. The output unit 1007 includes a speaker, a display, and the like. The recording unit 1008 includes an auxiliary storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The communication unit 1009 includes a communication module compatible with communication methods such as wireless LAN (Local Area Network), cellular communication (for example, 5G, etc.), Bluetooth (registered trademark), and the like. A drive 1010 drives a removable medium 1011 such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory.

In the computer 1000 configured as described above, the CPU 1001 loads a program recorded in the ROM 1002 and the recording unit 1008 into the RAM 1003 via the input/output interface 1005 and the bus 1004, and executes it. A series of processes are performed.

The program executed by the computer 1000 (CPU 1001) can be provided by being recorded on removable media 1011 such as package media, for example. Also, the program can be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

In the computer 1000 , the program can be installed in the recording unit 1008 via the input/output interface 1005 by loading the removable medium 1011 into the drive 1010 . Also, the program can be received by the communication unit 1009 via a wired or wireless transmission medium and installed in the recording unit 1008 . In addition, programs can be installed in the ROM 1002 and the recording unit 1008 in advance.

Here, in this specification, processing performed by a computer according to a program also includes processing that is executed in parallel or individually (for example, parallel processing or processing by objects). Also, the program may be processed by one computer (processor) or may be processed by a plurality of computers in a distributed manner.

In addition, each step of the series of processes in estimating the self-position and orientation described above can be performed by one device or shared by a plurality of devices. Furthermore, when one step includes a plurality of processes, the plurality of processes included in the one step can be executed by one device or shared by a plurality of devices.

It should be noted that the embodiment of the present technology is not limited to the embodiment described above, and various modifications are possible without departing from the gist of the present disclosure. Moreover, the effects described in this specification are merely examples and are not limited, and other effects may be provided.

It should be noted that the present disclosure can be configured as follows.

(1)
at least two absolute position sensors;
a self-position/orientation calculator that calculates the self-position and orientation,
The information processing apparatus, wherein the self position and orientation calculation unit calculates the self position and orientation based on the absolute position obtained from the absolute position sensor and the relative position of the absolute position sensor with respect to a reference position of the mobile device.
(2)
The information processing apparatus according to (1), wherein the absolute position sensor is an optical absolute position sensor installed so as to be able to recognize a predetermined pattern formed on a moving surface on which the moving device can move.
(3)
the absolute position includes at least the coordinates of the optical absolute position sensor;
The information processing apparatus according to (2), wherein the optical absolute position sensor identifies the coordinates by recognizing the predetermined pattern.
(4)
The information processing apparatus according to (2) or (3), wherein the predetermined pattern includes a predetermined pattern indicating an absolute position formed on a mat or a floor surface.
(5)
the reference position is the center of the bottom surface of the moving device;
The information processing apparatus according to any one of (1) to (4), wherein the absolute position sensor is arranged with reference to the center of the bottom surface of the mobile device.
(6)
The information processing apparatus according to any one of (1) to (5), wherein the mobile device operates in synchronization with one or more other mobile devices.
(7)
The information processing device
An information processing method, comprising: calculating a self position and orientation of the mobile device based on absolute positions obtained from at least two absolute position sensors and relative positions of the absolute position sensors with respect to a reference position of the mobile device.
(8)
the computer,
Functioning as a self-position/orientation calculator that calculates the self-position and orientation of the mobile device based on the absolute positions obtained from at least two or more absolute position sensors and the relative positions of the absolute position sensors with respect to the reference position of the mobile device. A program that makes
(9)
at least two absolute position sensors;
A mobile device, comprising: a control unit that calculates its own position and orientation based on the absolute position acquired from the absolute position sensor and the relative position of the absolute position sensor with respect to its own reference position.
(10)
a mobile device;
and an absolute position detection mat on which a predetermined pattern indicating an absolute position is formed,
The moving device
at least two absolute position sensors;
a control unit that calculates the self-position and orientation based on the absolute position acquired from the absolute position sensor and the relative position of the absolute position sensor with respect to the self-reference position,
An information processing system that identifies the absolute position by recognizing the pattern with the absolute position sensor when the mobile device is present on the absolute position detection mat.
(11)
The information processing system according to (10), wherein the absolute position detection mat has an infrared pattern indicating the absolute position.

10 Robot device, 20 Absolute position detection mat, 30 Coat, 101 Control unit, 102 Video display unit, 103 Screen lifting unit, 104-1 Left motor encoder, 104-2 Right motor encoder, 105-1 Left motor, 105- 2 Right motor, 106-1 to 106-3, 106 sensor, 107 battery unit, 151 main CPU, 152 sensor, 161, 161-1 to 161-N optical absolute position sensor, 171 self-position/orientation calculator, 172 control Department, 1000 Computer, 1001 CPU

Claims

at least two absolute position sensors;
a self-position/orientation calculator that calculates the self-position and orientation,
The information processing apparatus, wherein the self position and orientation calculation unit calculates the self position and orientation based on the absolute position obtained from the absolute position sensor and the relative position of the absolute position sensor with respect to a reference position of the mobile device.
The information processing apparatus according to claim 1, wherein the absolute position sensor is an optical absolute position sensor installed so as to be able to recognize a predetermined pattern formed on a moving surface on which the moving device can move.
the absolute position includes at least the coordinates of the optical absolute position sensor;
The information processing apparatus according to claim 2, wherein the optical absolute position sensor identifies the coordinates by recognizing the predetermined pattern.
3. The information processing apparatus according to claim 2, wherein the predetermined pattern includes a pattern indicating an absolute position formed on a mat or a floor surface.
the reference position is the center of the bottom surface of the moving device;
The information processing device according to claim 1, wherein the absolute position sensor is arranged with reference to the center of the bottom surface of the mobile device.
2. The information processing apparatus of claim 1, wherein the mobile device operates synchronously with one or more other mobile devices.
The information processing device
An information processing method, comprising: calculating a self position and orientation of the mobile device based on absolute positions obtained from at least two absolute position sensors and relative positions of the absolute position sensors with respect to a reference position of the mobile device.
the computer,
Functioning as a self-position/orientation calculator that calculates the self-position and orientation of the mobile device based on the absolute positions obtained from at least two or more absolute position sensors and the relative positions of the absolute position sensors with respect to the reference position of the mobile device. A program that makes
at least two absolute position sensors;
A mobile device, comprising: a control unit that calculates its own position and orientation based on the absolute position acquired from the absolute position sensor and the relative position of the absolute position sensor with respect to its own reference position.
a mobile device;
and an absolute position detection mat on which a predetermined pattern indicating an absolute position is formed,
The moving device
at least two absolute position sensors;
a control unit that calculates the self-position and orientation based on the absolute position obtained from the absolute position sensor and the relative position of the absolute position sensor with respect to the self-reference position,
An information processing system that identifies the absolute position by recognizing the pattern with the absolute position sensor when the mobile device is present on the absolute position detection mat.
11. The information processing system according to claim 10, wherein said absolute position detection mat has an infrared pattern indicating said absolute position.